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--- |
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library_name: transformers |
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base_model: unsloth/tinyllama-bnb-4bit |
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license: mit |
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datasets: |
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- yahma/alpaca-cleaned |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- Instruct |
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- TinyLlama |
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--- |
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# Steps to try the model: |
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### prompt Template |
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```python |
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alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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{} |
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### Input: |
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{} |
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### Response: |
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{}""" |
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``` |
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### load the model |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("damerajee/tinyllama-sft-small-v2") |
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model = AutoModelForCausalLM.from_pretrained("damerajee/tinyllama-sft-small-v2") |
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``` |
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### Inference |
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```python |
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inputs = tokenizer( |
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[ |
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alpaca_prompt.format( |
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"best places to visit in india", # instruction |
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"", # input |
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"", # output |
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) |
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]*1, return_tensors = "pt") |
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outputs = model.generate(**inputs, max_new_tokens = 128, use_cache = True) |
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tokenizer.batch_decode(outputs) |
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``` |
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# Model Information |
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The base model [unsloth/tinyllama-bnb-4bit](https://huggingface.co/unsloth/tinyllama-bnb-4bit) was Instruct finetuned using [Unsloth](https://github.com/unslothai/unsloth) |
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# Model Limitations |
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The model was trained on a very small dataset so it might not be as good ,will be training on larger dataset soon |
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# Training Details |
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The model was trained for 1 epoch on a free goggle colab which took about 1 hour and 30 mins approximately |